Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns

Symptom Network Analysis and Unsupervised Clustering of Oncology Patients Identifies Drivers of Symptom Burden and Patient Subgroups With Distinct Symptom Patterns

ABSTRACT Background Interindividual variability in oncology patients' symptom experiences poses significant challenges in prioritizing symptoms for targeted intervention(s). In this study, computational approaches were used to unbiasedly characterize the heterogeneity of the symptom experience...

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Bibliographic Details
Main Authors: Brandon H. Bergsneider, Terri S. Armstrong, Yvette P. Conley, Bruce Cooper, Marilyn Hammer, Jon D. Levine, Steven Paul, Christine Miaskowski, Orieta Celiku
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Cancer Medicine
Subjects:
Gaussian graphical models
network analysis
precision medicine
quality of life
Online Access:https://doi.org/10.1002/cam4.70278
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https://doi.org/10.1002/cam4.70278

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